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OCT Fluid Segmentation using Graph Shortest Path and Convolutional Neural Network.

Abdolreza Rashno, Dara D Koozekanani, Keshab K Parhi

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |November 17, 2018
    PubMed
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    This study introduces an automated method using graph shortest path and CNNs to detect and segment retinal fluid (SRF, IRF, PED) in OCT B-scans. The approach shows high accuracy in diagnosing conditions like AMD and diabetic retinopathy.

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    Area of Science:

    • Ophthalmology
    • Medical Imaging
    • Artificial Intelligence

    Background:

    • Optical coherence tomography (OCT) is crucial for diagnosing retinal diseases characterized by fluid accumulation.
    • Accurate segmentation of sub-retinal fluid (SRF), intra-retinal fluid (IRF), and pigment epithelium detachment (PED) is essential for monitoring conditions like age-related macular degeneration (AMD) and diabetic retinopathy (DR).

    Purpose of the Study:

    • To develop and validate a fully-automated method for segmenting and detecting three types of retinal fluid (SRF, IRF, PED) in OCT B-scans.
    • To assess the method's performance across different OCT datasets and a clinical challenge.

    Main Methods:

    • A novel approach combining graph shortest path algorithms and convolutional neural networks (CNNs) was employed.
    • The method was trained and tested on OCT B-scans from Cirrus, Spectralis, and Topcon datasets, including images from the 2017 Retouch challenge.

    Main Results:

    • The automated method achieved high segmentation accuracy, with average Dice coefficients of 76.44% (Cirrus), 92.25% (Spectralis), and 82.14% (Topcon).
    • The system demonstrated effectiveness in segmenting retinal fluid in challenging OCT images from the Retouch challenge.

    Conclusions:

    • The proposed automated method offers a robust and accurate solution for segmenting and detecting key fluid types in OCT B-scans.
    • This technology has the potential to significantly aid in the diagnosis and monitoring of major retinal pathologies.